How to compare electricity charts fairly

Two charts can look related without measuring the same thing. Before comparing them, check the metric, unit, timestamps, sampling interval and available coverage. These checks matter especially when switching between the dashboard and an hourly archive.

Power is not energy

A reading of 10 GW describes a rate of output. If that rate remained constant for two hours, it would supply 20 GWh. One 10 GW observation does not establish the energy supplied over those hours. An arithmetic sample mean is also not automatically an energy total, particularly if observations are unevenly spaced.

An hourly point can miss a peak

Imagine observations of 30 GW at 12:00, 40 GW at 12:10 and 31 GW at 12:59. Keeping the latest observation in that hour retains 31 GW and hides the 40 GW peak. This is why a full-resolution maximum and an hourly-archive maximum can differ without either chart being calculated incorrectly.

A gap is not a zero

If ten minutes of wind output are missing, those minutes are unknown; they do not mean generation stopped. There is an additional limitation in this site’s legacy collector: it substitutes zero for some unparsed generation fields and 50 Hz for unparsed frequency. A numerical record therefore does not by itself prove successful parsing. The display cannot retrospectively identify every substituted value.

Compare like periods

Suppose a selected period has 1,400 usable minute records but the comparison has 900. Their means reflect different coverage, and missing observations may affect the difference. Inspect coverage alongside the values. Around a clock change, equal calendar dates can cover different elapsed durations. State which comparison you chose.

Wind and gas: association is not proof

If wind falls while gas rises, report both recorded changes. The charts alone do not establish that the gas was dispatched specifically to replace that wind. Demand, interconnector flows, storage, station availability and trading can change at the same time. An honest analysis distinguishes measured differences from explanations that require other evidence.

Compare generation history · Sampling methodology · All guides